By learning neuron positions and computing weights from spatial distance, the paper builds O(n)-parameter MLPs and spiking networks that are competitive on MNIST and robust to pruning, but not more accurate than standard MLPs.
Nature Communications 13 (2022)
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Training Neural Networks by Optimizing Neuron Positions
By learning neuron positions and computing weights from spatial distance, the paper builds O(n)-parameter MLPs and spiking networks that are competitive on MNIST and robust to pruning, but not more accurate than standard MLPs.